Digital Twin for Variation Management: A General Framework and Identification of Industrial Challenges Related to the Implementation

Digital twins have gained a lot of interest in recent years. This paper presents a survey among researchers and engineers with expertise in variation management confirming the interest of digital twins in this area. The survey shows, however, a gap between future research interest in academia and industry, identifying a larger need in industry. This indicates that there are some barriers in the industry to overcome before the benefits of a digital twin for variation management and geometry assurance can be fully capitalized on in an industrial context. To identify those barriers and challenges, an extensive interview study with engineers from eight different companies in the manufacturing sectors was accomplished. The analysis identifies industrial challenges in the areas of system-level, simulation working process, management issues, and education. One of the main challenges is to keep the 3D models fully updated, including keeping track of changes during the product development process and also feedback changes during full production to the development engineers. This is a part of what is called the digital thread, which is also addressed in this paper

Criteria for Assessment of Basic Manual Assembly Complexity

AbstractTough competition force companies to develop and increase their product assortment in order to maintain their market share. This has resulted in numerous product variants with more features and build options. The complexity and risk of quality errors will increase. Managing complex product and installation conditions will result in distinct competitive advantages. Research has shown that sustainable and more cost-efficient assembly solutions can be obtained by proactive improvement of the working environment and installation conditions for the operators. Significant reduction of costly corrective measures can be made. The objective of this paper was to demonstrate criteria for proactive assessment of manual assembly complexity, which have been developed and verified in several studies. A further objective was to clarify and quantify included criteria as far as possible to enable a more general application in manual mass production of complex products

Robust design of aero engine structures: Transferring form error data when mapping out design spaces for new turbine components

In aerospace modeling and simulation, nominal geometries are norm. However, it has been shown that form error, or irregular deviations in geometry, aggravates thermal stresses, which in turn reduces product life. While form error can be measured on manufactured products using 3D laser scanners, a simulation infrastructure is needed to analyze its effects on aerodynamic, structural and thermal performance. Moreover, in early product development phases, before manufacturing has begun, form error data is not available. This paper describes a method for including form error data in mainstream simulation activities. The suggested method works by creating parametric CAD-models to accommodate form error. There are two main benefits of this method. Firstly, it enables proactive robustness simulations where substantial design changes can be tested and evaluated. Secondly, it enables the mapping of data from previous products onto new designs, which means that robustness analyses can be performed in earlier design phases. To demonstrate this capability, a case study shows how a robust optimization scheme using genetic algorithms can improve product robustness to form error. The results show that form error have effects of the same order of magnitude as key design parameter changes. This finding underlines the importance of performing form error analyses in exploratory early design phases

Variation Analysis considering manual assembly complexity in a CAT tool.

Virtual geometry assurance is a key component of today´s product development. Much of the virtual geometry assurance is done in Computer Aided Tolerancing (CAT) tools. Earlier research has shown that manual assembly complexity influences the geometrical quality of the product and that assembly tolerances are seldom used in CAT simulations for manual assembly parts. In this study a method for including manual assembly complexity in variation analysis in CAT is introduced and discussed.The method has been tested and implemented in a CAT tool using a real industrial case with promising results

Joining in Nonrigid Variation Simulation

Geometrical variation is closely related to fulfillment of both functional and esthetical requirements on the final product. To investigate the fulfillment of those requirements, Monte Carlo (MC)-based variation simulations can be executed in order to predict the levels of geometrical variation on subassembly and/or product level. If the variation simulations are accurate enough, physical tests and try-outs can be replaced, which reduce cost and lead-time. To ensure high accuracy, the joining process is important to include in the variation simulation. In this chapter, an overview of nonrigid variation simulation is given and aspects such as the type and number of joining points, the joining sequence and joining forces are discussed

Automotive UX design and data-driven development: Narrowing the gap to support practitioners

The development and evaluation of In-Vehicle Information Systems (IVISs) is strongly based on insights from qualitative studies conducted in artificial contexts (e.g., driving simulators or lab experiments). However, the growing complexity of the systems and the uncertainty about the context in which they are used, create a need to augment qualitative data with quantitative data, collected during real-world driving. In contrast to many digital companies that are already successfully using data-driven methods, Original Equipment Manufacturers (OEMs) are not yet succeeding in releasing the potentials such methods offer. We aim to understand what prevents automotive OEMs from applying data-driven methods, what needs practitioners formulate, and how collecting and analyzing usage data from vehicles can enhance UX activities. We adopted a Multiphase Mixed Methods approach comprising two interview studies with more than 15 UX practitioners and two action research studies conducted with two different OEMs. From the four studies, we synthesize the needs of UX designers, extract limitations within the domain that hinder the application of data-driven methods, elaborate on unleveraged potentials, and formulate recommendations to improve the usage of vehicle data. We conclude that, in addition to modernizing the legal, technical, and organizational infrastructure, UX and Data Science must be brought closer together by reducing silo mentality and increasing interdisciplinary collaboration. New tools and methods need to be developed and UX experts must be empowered to make data-based evidence an integral part of the UX design process

Tolerancing: Managing uncertainty from conceptual design to final product

Variability is unavoidable in the realization of products. While design must specify ideal geometry, it shall also describe limits of variability (tolerances) that must be met in order to maintain proper product function. Although tolerancing is a mature field, new manufacturing processes and design methodologies are creating new avenues of research, and modelling standards must also evolve to support these processes. In addition, the study of uncertainty has produced widely-accepted methods of quantifying variability, and modern tolerancing tools should support these methods. The challenges introduced by new processes and design methodologies continue to make tolerancing research a fertile and productive area

Editorial

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